Estimating Intra-Party Preferences: Comparing Speeches to Votes

Well-established methods exist for measuring party positions, but reliable means for estimating intra-party preferences remain underdeveloped. While most efforts focus on estimating the ideal points of individual legislators based on inductive scaling of roll call votes, this data suffers from two problems: selection bias due to unrecorded votes and strong party discipline, which tends to make voting a strategic rather than a sincere indication of preferences. By contrast, legislative speeches are relatively unconstrained, as party leaders are less likely to punish MPs for speaking freely as long as they vote with the party line. Yet, the differences between roll call estimations and text scalings remain essentially unexplored, despite the growing application of statistical analysis of textual data to measure policy preferences. Our paper addresses this lacuna by exploiting a rich feature of the Swiss legislature: on most bills, legislators both vote and speak many times. Using this data, we compare text-based scaling of ideal points to vote-based scaling from a crucial piece of energy legislation. Our findings confirm that text scalings reveal larger intra-party differences than roll calls. Using regression models, we further explain the differences between roll call and text scalings by attributing differences to constituency-level preferences for energy policy.

Community College Student Participation in Undergraduate Research: An Explanatory Case Study for Faculty and Research Mentors

This study adapted the current model of science undergraduate research experiences (URE's) and applied this novel modification to include community college students. Numerous researchers have examined the efficacy of URE's in improving undergraduate retention and graduation rates, as well as matriculation rates for graduate programs. However, none have detailed the experience for community college students, and few have employed qualitative methodologies to gather relevant descriptive data from URE participants. This study included perspectives elicited from both non-traditional student participants and the established laboratory community. The purpose of this study was to determine the effectiveness of the traditional model for a non-traditional student population. The research effort described here utilized a qualitative design and an explanatory case study methodology. Six non-traditional students from the Maine Community College System participated in this study. Student participants were placed in six academic research laboratories located throughout the state. Student participants were interviewed three times during their ten-week internship and asked to record their personal reflections in electronic format. Participants from the established research community were also interviewed. These included both faculty mentors and other student laboratory personnel. Ongoing comparative analysis of the textual data revealed that laboratory organizational structure and social climate significantly influence acculturation outcomes for non-traditional URE participants. Student participants experienced a range of acculturation outcomes from full integration to marginalization. URE acculturation outcomes influenced development of non-traditional students? professional and academic self-concepts. Positive changes in students? self-concepts resulted in greater commitment to individual professional goals and academic aspirations. The findings from this study suggest that traditional science URE models can be successfully adapted to meet the unique needs of a non-traditional student population – community college students. These interpretations may encourage post-secondary educators, administrators, and policy makers to consider expanded access and support for non-traditional students seeking science URE opportunities.

USO DE TEORIAS NO CAMPO DE SISTEMAS DE INFORMAÇÃO: MAPEAMENTO USANDO TÉCNICAS DE MINERAÇÃO DE TEXTOS

Esta dissertação visa apresentar o mapeamento do uso das teorias de sistemas de informações, usando técnicas de recuperação de informação e metodologias de mineração de dados e textos. As teorias abordadas foram Economia de Custos de Transações (Transactions Costs Economics TCE), Visão Baseada em Recursos da Firma (Resource-Based View-RBV) e Teoria Institucional (Institutional Theory-IT), sendo escolhidas por serem teorias de grande relevância para estudos de alocação de investimentos e implementação em sistemas de informação, tendo como base de dados o conteúdo textual (em inglês) do resumo e da revisão teórica dos artigos dos periódicos Information System Research (ISR), Management Information Systems Quarterly (MISQ) e Journal of Management Information Systems (JMIS) no período de 2000 a 2008. Os resultados advindos da técnica de mineração textual aliada à mineração de dados foram comparadas com a ferramenta de busca avançada EBSCO e demonstraram uma eficiência maior na identificação de conteúdo. Os artigos fundamentados nas três teorias representaram 10% do total de artigos dos três períodicos e o período mais profícuo de publicação foi o de 2001 e 2007.(AU)

USO DE TEORIAS NO CAMPO DE SISTEMAS DE INFORMAÇÃO: MAPEAMENTO USANDO TÉCNICAS DE MINERAÇÃO DE TEXTOS

Esta dissertação visa apresentar o mapeamento do uso das teorias de sistemas de informações, usando técnicas de recuperação de informação e metodologias de mineração de dados e textos. As teorias abordadas foram Economia de Custos de Transações (Transactions Costs Economics TCE), Visão Baseada em Recursos da Firma (Resource-Based View-RBV) e Teoria Institucional (Institutional Theory-IT), sendo escolhidas por serem teorias de grande relevância para estudos de alocação de investimentos e implementação em sistemas de informação, tendo como base de dados o conteúdo textual (em inglês) do resumo e da revisão teórica dos artigos dos periódicos Information System Research (ISR), Management Information Systems Quarterly (MISQ) e Journal of Management Information Systems (JMIS) no período de 2000 a 2008. Os resultados advindos da técnica de mineração textual aliada à mineração de dados foram comparadas com a ferramenta de busca avançada EBSCO e demonstraram uma eficiência maior na identificação de conteúdo. Os artigos fundamentados nas três teorias representaram 10% do total de artigos dos três períodicos e o período mais profícuo de publicação foi o de 2001 e 2007.(AU)

USO DE TEORIAS NO CAMPO DE SISTEMAS DE INFORMAÇÃO: MAPEAMENTO USANDO TÉCNICAS DE MINERAÇÃO DE TEXTOS

Esta dissertação visa apresentar o mapeamento do uso das teorias de sistemas de informações, usando técnicas de recuperação de informação e metodologias de mineração de dados e textos. As teorias abordadas foram Economia de Custos de Transações (Transactions Costs Economics TCE), Visão Baseada em Recursos da Firma (Resource-Based View-RBV) e Teoria Institucional (Institutional Theory-IT), sendo escolhidas por serem teorias de grande relevância para estudos de alocação de investimentos e implementação em sistemas de informação, tendo como base de dados o conteúdo textual (em inglês) do resumo e da revisão teórica dos artigos dos periódicos Information System Research (ISR), Management Information Systems Quarterly (MISQ) e Journal of Management Information Systems (JMIS) no período de 2000 a 2008. Os resultados advindos da técnica de mineração textual aliada à mineração de dados foram comparadas com a ferramenta de busca avançada EBSCO e demonstraram uma eficiência maior na identificação de conteúdo. Os artigos fundamentados nas três teorias representaram 10% do total de artigos dos três períodicos e o período mais profícuo de publicação foi o de 2001 e 2007.(AU)

Examining argumentative coherence in essays by undergraduate students of English as a foreign language in Mainland China and their English speaking peers in the United States

I conducted this study to provide insights toward deepening understanding of association between culture and writing by building, assessing, and refining a conceptual model of second language writing. To do this, I examined culture and coherence as well as the relationship between them through a mixed methods research design. Coherence has been an important and complex concept in ESL/EFL writing. I intended to study the concept of coherence in the research context of contrastive rhetoric, comparing the coherence quality in argumentative essays written by undergraduates in Mainland China and their U.S. peers. In order to analyze the complex concept of coherence, I synthesized five linguistic theories of coherence: Halliday and Hasan's cohesion theory, Carroll's theory of coherence, Enkvist's theory of coherence, Topical Structure Analysis, and Toulmin's Model. Based upon the synthesis, 16 variables were generated. Across these 16 variables, Hotelling t-test statistical analysis was conducted to predict differences in argumentative coherence between essays written by two groups of participants. In order to complement the statistical analysis, I conducted 30 interviews of the writers in the studies. Participants' responses were analyzed with open and axial coding. By analyzing the empirical data, I refined the conceptual model by adding more categories and establishing associations among them. The study found that U.S. students made use of more pronominal reference. Chinese students adopted more lexical devices of reiteration and extended paralleling progression. The interview data implied that the difference may be associated with the difference in linguistic features and rhetorical conventions in Chinese and English. As far as Toulmin's Model is concerned, Chinese students scored higher on data than their U.S. peers. According to the interview data, this may be due to the fact that Toulmin's Model, modified as three elements of arguments, have been widely and long taught in Chinese writing instruction while U.S. interview participants said that they were not taught to write essays according to Toulmin's Model. Implications were generated from the process of textual data analysis and the formulation of structural model defining coherence. These implications were aimed at informing writing instruction, assessment, peer-review, and self-revision.

Full of Hot Air? Three Examinations of Climate Change in the American Political Information Environment

Climate change is thought to be one of the most pressing environmental problems facing humanity. However, due in part to failures in political communication and how the issue has been historically defined in American politics, discussions of climate change remain gridlocked and polarized. In this dissertation, I explore how climate change has been historically constructed as a political issue, how conflicts between climate advocates and skeptics have been communicated, and what effects polarization has had on political communication, particularly on the communication of climate change to skeptical audiences. I use a variety of methodological tools to consider these questions, including evolutionary frame analysis, which uses textual data to show how issues are framed and constructed over time; Kullback-Leibler divergence content analysis, which allows for comparison of advocate and skeptical framing over time; and experimental framing methods to test how audiences react to and process different presentations of climate change. I identify six major portrayals of climate change from 1988 to 2012, but find that no single construction of the issue has dominated the public discourse defining the problem. In addition, the construction of climate change may be associated with changes in public political sentiment, such as greater pessimism about climate action when the electorate becomes more conservative. As the issue of climate change has become more polarized in American politics, one proposed causal pathway for the observed polarization is that advocate and skeptic framing of climate change focuses on different facets of the issue and ignores rival arguments, a practice known as “talking past.” However, I find no evidence of increased talking past in 25 years of popular newsmedia reporting on the issue, suggesting both that talking past has not driven public polarization or that polarization is occurring in venues outside of the mainstream public discourse, such as blogs. To examine how polarization affects political communication on climate change, I test the cognitive processing of a variety of messages and sources that promote action against climate change among Republican individuals. Rather than identifying frames that are powerful enough to overcome polarization, I find that Republicans exhibit telltale signs of motivated skepticism on the issue, that is, they reject framing that runs counter to their party line and political identity. This result suggests that polarization constrains political communication on polarized issues, overshadowing traditional message and source effects of framing and increasing the difficulty communicators experience in reaching skeptical audiences.

Assisting digital forensic analysis via exploratory information visualisation

Background: Digital forensics is a rapidly expanding field, due to the continuing advances in computer technology and increases in data stage capabilities of devices. However, the tools supporting digital forensics investigations have not kept pace with this evolution, often leaving the investigator to analyse large volumes of textual data and rely heavily on their own intuition and experience. Aim: This research proposes that given the ability of information visualisation to provide an end user with an intuitive way to rapidly analyse large volumes of complex data, such approached could be applied to digital forensics datasets. Such methods will be investigated; supported by a review of literature regarding the use of such techniques in other fields. The hypothesis of this research body is that by utilising exploratory information visualisation techniques in the form of a tool to support digital forensic investigations, gains in investigative effectiveness can be realised. Method:To test the hypothesis, this research examines three different case studies which look at different forms of information visualisation and their implementation with a digital forensic dataset. Two of these case studies take the form of prototype tools developed by the researcher, and one case study utilises a tool created by a third party research group. A pilot study by the researcher is conducted on these cases, with the strengths and weaknesses of each being drawn into the next case study. The culmination of these case studies is a prototype tool which was developed to resemble a timeline visualisation of the user behaviour on a device. This tool was subjected to an experiment involving a class of university digital forensics students who were given a number of questions about a synthetic digital forensic dataset. Approximately half were given the prototype tool, named Insight, to use, and the others given a common open-source tool. The assessed metrics included: how long the participants took to complete all tasks, how accurate their answers to the tasks were, and how easy the participants found the tasks to complete. They were also asked for their feedback at multiple points throughout the task. Results:The results showed that there was a statistically significant increase in accuracy for one of the six tasks for the participants using the Insight prototype tool. Participants also found completing two of the six tasks significantly easier when using the prototype tool. There were no statistically significant different difference between the completion times of both participant groups. There were no statistically significant differences in the accuracy of participant answers for five of the six tasks. Conclusions: The results from this body of research show that there is evidence to suggest that there is the potential for gains in investigative effectiveness when information visualisation techniques are applied to a digital forensic dataset. Specifically, in some scenarios, the investigator can draw conclusions which are more accurate than those drawn when using primarily textual tools. There is also evidence so suggest that the investigators found these conclusions to be reached significantly more easily when using a tool with a visual format. None of the scenarios led to the investigators being at a significant disadvantage in terms of accuracy or usability when using the prototype visual tool over the textual tool. It is noted that this research did not show that the use of information visualisation techniques leads to any statistically significant difference in the time taken to complete a digital forensics investigation.

Injuries leading to hospitalisation in the first year of life : analysis by trimester of age using coded data and textual description

Objective: To describe unintentional injuries to children aged less than one year, using coded and textual information, in three-month age bands to reflect their development over the year. Methods: Data from the Queensland Injury Surveillance Unit was used. The Unit collects demographic, clinical and circumstantial details about injured persons presenting to selected emergency departments across the State. Only injuries coded as unintentional in children admitted to hospital were included for this analysis. Results: After editing, 1,082 children remained for analysis, 24 with transport-related injuries. Falls were the most common injury, but becoming proportionately less over the year, whereas burns and scalds and foreign body injuries increased. The proportion of injuries due to contact with persons or objects varied little, but poisonings were relatively more common in the first and fourth three-month periods. Descriptions indicated that family members were somehow causally involved in 16% of injuries. Our findings are in qualitative agreement with comparable previous studies. Conclusion: The pattern of injuries varies over the first year of life and is clearly linked to the child's increasing mobility. Implications: Injury patterns in the first year of life should be reported over shorter intervals. Preventive measures for young children need to be designed with their rapidly changing developmental stage in mind, using a variety of strategies, one of which could be opportunistic developmentally specific education of parents. Injuries in young children are of abiding concern given their immediate health and emotional effects, and potential for long-term adverse sequelae. In Australia, in the financial year 2006/07, 2,869 children less than 12 months of age were admitted to hospital for an unintentional injury, a rate of 10.6 per 1,000, representing a considerable economic and social burden. Given that many of these injuries are preventable, this is particularly concerning. Most epidemiologic studies analyse data in five-year age bands, so children less than five years of age are examined as a group. This study includes only those children younger than one year of age to identify injury detail lost in analyses of the larger group, as we hypothesised that the injury pattern varied with the developmental stage of the child. The authors of several North American studies have commented that in dealing with injuries in pre-school children, broad age groupings are inadequate to do justice to the rapid developmental changes in infancy and early childhood, and have in consequence analysed injuries in shorter intervals. To our knowledge, no similar analysis of Australian infant injuries has been published to date. This paper describes injury in children less than 12 months of age using data from the Queensland Injury Surveillance Unit (QISU).

Using data mining to improve building life cycle

The building life cycle process is complex and prone to fragmentation as it moves through its various stages. The number of participants, and the diversity, specialisation and isolation both in space and time of their activities, have dramatically increased over time. The data generated within the construction industry has become increasingly overwhelming. Most currently available computer tools for the building industry have offered productivity improvement in the transmission of graphical drawings and textual specifications, without addressing more fundamental changes in building life cycle management. Facility managers and building owners are primarily concerned with highlighting areas of existing or potential maintenance problems in order to be able to improve the building performance, satisfying occupants and minimising turnover especially the operational cost of maintenance. In doing so, they collect large amounts of data that is stored in the building’s maintenance database. The work described in this paper is targeted at adding value to the design and maintenance of buildings by turning maintenance data into information and knowledge. Data mining technology presents an opportunity to increase significantly the rate at which the volumes of data generated through the maintenance process can be turned into useful information. This can be done using classification algorithms to discover patterns and correlations within a large volume of data. This paper presents how and what data mining techniques can be applied on maintenance data of buildings to identify the impediments to better performance of building assets. It demonstrates what sorts of knowledge can be found in maintenance records. The benefits to the construction industry lie in turning passive data in databases into knowledge that can improve the efficiency of the maintenance process and of future designs that incorporate that maintenance knowledge.

The cultural impact of institutional remix : the formalisation of textual reappropriation within the ABC

In 2009, Mark Deuze proposed an updated approach to media studies to incorporate ‘media life’, a concept he suggests addresses the invisibleness of ubiquitous media. Media life provides a useful lens for researchers to understand the human condition in media and not with media. At a similar time, public service media (PSM) strategies have aligned audience participation with the so‐called Reithian trinity which suggest the PSB should inform, educate and entertain while performing its core values of public service broadcasting (Enli 2008). Remix within the PSM institution relies on audience participation, employing ‘the people formerly known as the audience’ (Rosen 2006) as cultural artifact producers, and draws on their experience from within the media. Remix as a practice then enables us to examine the shift of the core PSM values by understanding how audience participation, informed by a human condition mobilised from our existence of being in media and not merely with media. However, remix within PSM challenges the once elitist construction of meaning models with an egalitarian approach towards socially reappropriated texts, questioning its affect on the cultural landscape. This paper draws on three years of ethnographic data from within the Australian Broadcasting Corporation (ABC), exploring the remix culture of ABC Pool. ABC Pool operates under a Creative Commons licensing regime to enable remix practice under the auspices of the ABC. ABC Pool users provide a useful group of remix practitioners to examine as they had access to a vast ABC archival collection and were invited to remix those cultural artefacts, often adding cultural and fiscal value. This paper maintains a focus on the audience participation within PSM through remix culture by applying media dependency theory to remix as cultural practice and calls to expand and update the societal representation within the ABC.

Cultural flows in an Aboriginal school : deterritorializing textual production through a socially mediated Indigenous heritage

Flows of cultural heritage in textual practices are vital to sustaining Indigenous communities. Indigenous heritage, whether passed on by oral tradition or ubiquitous social media, can be seen as a “conversation between the past and the future” (Fairclough, 2012, xv). Indigenous heritage involves appropriating memories within a cultural flow to pass on a spiritual legacy. This presentation reports ethnographic research of social media practices in a small independent Aboriginal school in Southeast Queensland, Australia that is resided over by the Yugambeh elders and an Aboriginal principal. The purpose was to rupture existing notions of white literacies in schools, and to deterritorialize the uses of digital media by dominant cultures in the public sphere. Examples of learning experiences included the following: i. Integrating Indigenous language and knowledge into media text production; ii. Using conversations with Indigenous elders and material artifacts as an entry point for storytelling; iii. Dadirri – spiritual listening in the yarning circle to develop storytelling (Ungunmerr-Baumann, 2002); and iv. Writing and publicly sharing oral histories through digital scrapbooking shared via social media. The program aligned with the Australian National Curriculum English (ACARA, 2012), which mandates the teaching of multimodal text creation. Data sources included a class set of digital scrapbooks collaboratively created in a multi-age primary classroom. The digital scrapbooks combined digitally encoded words, images of material artifacts, and digital music files. A key feature of the writing and digital design task was to retell and digitally display and archive a cultural narrative of significance to the Indigenous Australian community and its memories and material traces of the past for the future. Data analysis of the students’ digital stories involved the application of key themes of negotiated, material, and digitally mediated forms of heritage practice. It drew on Australian Indigenous research by Keddie et al. (2013) to guard against the homogenizing of culture that can arise from a focus on a static view of culture. The interpretation of findings located Indigenous appropriation of social media within broader racialized politics that enables Indigenous literacy to be understood as a dynamic, negotiated, and transgenerational flows of practice. The findings demonstrate that Indigenous children’s use of media production reflects “shifting and negotiated identities” in response to changing media environments that can function to sustain Indigenous cultural heritages (Appadurai, 1696, xv). It demonstrated how the children’s experiences of culture are layered over time, as successive generations inherit, interweave, and hear others’ cultural stories or maps. It also demonstrated how the children’s production of narratives through multimedia can provide a platform for the flow and reconstruction of performative collective memories and “lived traces of a common past” (Giaccardi, 2012). It disrupts notions of cultural reductionism and racial incommensurability that fix and homogenize Indigenous practices within and against a dominant White norm. Recommendations are provided for an approach to appropriating social media in schools that explicitly attends to the dynamic nature of Indigenous practices, negotiated through intercultural constructions and flows, and opening space for a critical anti-racist approach to multimodal text production.

Perception of prescription medicine sample packs among Australian professional, government, industry, and consumer organizations, based on automated textual analysis of one-on-one interviews

Background Prescription medicine samples provided by pharmaceutical companies are predominantly newer and more expensive products. The range of samples provided to practices may not represent the drugs that the doctors desire to have available. Few studies have used a qualitative design to explore the reasons behind sample use. Objective The aim of this study was to explore the opinions of a variety of Australian key informants about prescription medicine samples, using a qualitative methodology. Methods Twenty-three organizations involved in quality use of medicines in Australia were identified, based on the authors' previous knowledge. Each organization was invited to nominate 1 or 2 representatives to participate in semistructured interviews utilizing seeding questions. Each interview was recorded and transcribed verbatim. Leximancer v2.25 text analysis software (Leximancer Pty Ltd., Jindalee, Queensland, Australia) was used for textual analysis. The top 10 concepts from each analysis group were interrogated back to the original transcript text to determine the main emergent opinions. Results A total of 18 key interviewees representing 16 organizations participated. Samples, patient, doctor, and medicines were the major concepts among general opinions about samples. The concept drug became more frequent and the concept companies appeared when marketing issues were discussed. The Australian Pharmaceutical Benefits Scheme and cost were more prevalent in discussions about alternative sample distribution models, indicating interviewees were cognizant of budgetary implications. Key interviewee opinions added richness to the single-word concepts extracted by Leximancer. Conclusions Participants recognized that prescription medicine samples have an influence on quality use of medicines and play a role in the marketing of medicines. They also believed that alternative distribution systems for samples could provide benefits. The cost of a noncommercial system for distributing samples or starter packs was a concern. These data will be used to design further research investigating alternative models for distribution of samples.

Methods for Answer Extraction in Textual Question Answering

In this thesis we present and evaluate two pattern matching based methods for answer extraction in textual question answering systems. A textual question answering system is a system that seeks answers to natural language questions from unstructured text. Textual question answering systems are an important research problem because as the amount of natural language text in digital format grows all the time, the need for novel methods for pinpointing important knowledge from the vast textual databases becomes more and more urgent. We concentrate on developing methods for the automatic creation of answer extraction patterns. A new type of extraction pattern is developed also. The pattern matching based approach chosen is interesting because of its language and application independence. The answer extraction methods are developed in the framework of our own question answering system. Publicly available datasets in English are used as training and evaluation data for the methods. The techniques developed are based on the well known methods of sequence alignment and hierarchical clustering. The similarity metric used is based on edit distance. The main conclusions of the research are that answer extraction patterns consisting of the most important words of the question and of the following information extracted from the answer context: plain words, part-of-speech tags, punctuation marks and capitalization patterns, can be used in the answer extraction module of a question answering system. This type of patterns and the two new methods for generating answer extraction patterns provide average results when compared to those produced by other systems using the same dataset. However, most answer extraction methods in the question answering systems tested with the same dataset are both hand crafted and based on a system-specific and fine-grained question classification. The the new methods developed in this thesis require no manual creation of answer extraction patterns. As a source of knowledge, they require a dataset of sample questions and answers, as well as a set of text documents that contain answers to most of the questions. The question classification used in the training data is a standard one and provided already in the publicly available data.

Exploiting evidence from unstructured data to enhance master data management

Master data management (MDM) integrates data from multiple
structured data sources and builds a consolidated 360-
degree view of business entities such as customers and products.
Today’s MDM systems are not prepared to integrate
information from unstructured data sources, such as news
reports, emails, call-center transcripts, and chat logs. However,
those unstructured data sources may contain valuable
information about the same entities known to MDM from
the structured data sources. Integrating information from
unstructured data into MDM is challenging as textual references
to existing MDM entities are often incomplete and
imprecise and the additional entity information extracted
from text should not impact the trustworthiness of MDM
data.
In this paper, we present an architecture for making MDM
text-aware and showcase its implementation as IBM InfoSphere
MDM Extension for Unstructured Text Correlation,
an add-on to IBM InfoSphere Master Data Management
Standard Edition. We highlight how MDM benefits from
additional evidence found in documents when doing entity
resolution and relationship discovery. We experimentally
demonstrate the feasibility of integrating information from
unstructured data sources into MDM.